In many digital coding and decoding systems for audio signals, a non-uniform quantization, for example, a logarithmic quantization, is widely used to compress coded data rate.
If an orthogonal transformation, for example, a discrete cosine transformation (DCT), a discrete Fourier transformation (DFT) or the like, is applied to the audio signal, it will be expected that the coded data rate is greately compressed. The basic block diagrams of a system like this are shown in FIGS. 8A and 8B.
As shown in FIG. 8A, a coding portion 20 comprises a window circuit 1 including a frame buffer for receiving an input audio signal, an orthogonal transform circuit 2 such as a DCT, DFT or the like, quantization circuit 3, and a coder circuit 4 for outputting a coded signal.
In contrast, as shown in FIG. 8B, a decoding portion 30 comprises a decoder circuit 5, a dequantization circuit 6, an inverse orthogonal transformation circuit 7 using an inverse discrete fourier transformation (IDFT) or an inverse discrete cosine tranformation (IDCT), and a window circuit 8 including an adder. The coded signal is received by the decoding portion 30 so as to be decoded and outputted as an output audio signal.
In FIG. 8A, an audio signal sampled by a sampling signal is inputted to the window circuit 1 in which a predetermined number of samples is cut out from the input signal as a block for orthogonal transformation. Usually, each block contains 256 to 2048 samples and corresponds to a period of 11 to 43 msec at a sampling frequency of 48 kHz.
In FIGS. 9A and 9B, the wave forms of sound signals generated by musical instruments are shown. As shown in the drawings, the sound of these musical instruments contains steep transients in which there is a large variation in amplitude level, and the period of each transient is sufficiently short relative to the period of the block. Therefore, there coexist high and low level portions in the block. It should be noted that if the maximum level of the signal being processed is high, the step size of quantization will be wide. The signal so seperated in blocks is transformed in the orthogonal transformation circuit 2, then quantized in the quantization circuit 3.
When the signal is processed by the non-uniform quantization in which the number of quantization steps (bits) is lessened for data rate compression and the step size is necessarily widened, quantization noise occurs at the low level portions. FIG. 10 shows the distributions of the quantization noise in the time axis of the signal. As is apparent from the figure, the quantization noise by quantizing at the high level portions of the original signal, influences the entire block on the time axis, and the noise becomes over a power in a lesser level of .the original signal. As a result, the quantization noise is audible as a noise incidental to the transient of the signal.
As described above, a conventional system has a problem in that the quantization noise is easy to detect with the non-uniform quantization when an audio signal, especially one having extremely steep transients, is coded.